iamhero2709/LinearRegressionModel ? reverse-engineered prompt

Build me a complete linear regression project from scratch in Python using NumPy, with an end to end workflow that loads the Boston Housing dataset, checks the data, splits it into training and test sets, scales the features, trains the model with gradient descent, and then evaluates it with useful metrics like MSE, RMSE, MAE, and R squared.

I also want clear visualizations for the learning curve, predictions versus actual values, and residuals, plus a simple way to run everything from a main script. Please keep it well organized and easy to follow, and include a notebook version too so I can explore it step by step.

Make it feel like a clean learning project, not just a quick demo, and if you need to look up current docs online for anything, go ahead.